What is it about?

Novel optimization techniques which are associated with machine learning and evolutionary computations are not given much attention in astrodynamics and space engineering. We developed a method for trajectory optimization of space systems based on new adaptive mechanisms within the framework of evolutionary algorithms.

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Why is it important?

Our algorithm can discover space trajectories for satellites to travel from one orbit to another orbit in an optimal manner. The developed algorithm gives more optimal transfer trajectories in comparison to previously developed algorithms. In terms of optimality, our algorithm is more efficient because simulations show that the fuel consumption of the satellite is lower when following the outcome of our method. Also, compared with previous techniques, our approach provides faster transfers for space systems in their voyage.


This research was my solo effort, which I worked on independently during my post-doc. I am glad that I could bring what I had in my mind to attention and share it with the astrodynamics community. I am delighted that my research received positive feedback from the reviewers and the editorial boards. It made me realize that the idea that I am proposing is interesting for the community and it does worth expanding in the future as well.

Abolfazl Shirazi
Basque Center for Applied Mathematics (BCAM)

Read the Original

This page is a summary of: Adaptive Estimation of Distribution Algorithms for Low-Thrust Trajectory Optimization, Journal of Spacecraft and Rockets, August 2023, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/1.a35570.
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